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IPAD: Intensity potential for adaptive de-quantization

  • Jing Liu
  • , Guangtao Zhai
  • , Xiaokang Yang
  • , Menghan Hu
  • , Chang Wen Chen
  • Tianjin University
  • Shanghai Jiao Tong University
  • SUNY Buffalo

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Display devices at bit-depth of 10 or higher have been mature but the mainstream media source is still at bit-depth as low as 8. To accommodate the gap, the most economic solution is to render source at low bit-depth for high bit-depth display, which is essentially the procedure of de-quantization. Traditional methods, like zero-padding or bit replication, introduce annoying false contour artifacts. To better estimate the least-significant bits, later works use filtering or interpolation approaches, which exploit only limited neighbor information, can not thoroughly remove the false contours. In this paper, we propose a novel intensity potential field to model the complicated relationships among pixels. Then, an adaptive de-quantization algorithm is proposed to convert low bit-depth images to high bit-depth ones. To the best of our knowledge, this is the first attempt to apply potential field for natural images. The proposed potential field preserves local consistency and models the complicated contexts very well. Extensive experiments on natural image datasets validate the efficiency of the proposed intensity potential field. Significant improvements have been achieved over the state-of-the-art methods on both PSNR and SSIM.

源语言英语
主期刊名2017 IEEE International Conference on Multimedia and Expo, ICME 2017
出版商IEEE Computer Society
1207-1212
页数6
ISBN(电子版)9781509060672
DOI
出版状态已出版 - 28 8月 2017
已对外发布
活动2017 IEEE International Conference on Multimedia and Expo, ICME 2017 - Hong Kong, 香港
期限: 10 7月 201714 7月 2017

出版系列

姓名Proceedings - IEEE International Conference on Multimedia and Expo
ISSN(印刷版)1945-7871
ISSN(电子版)1945-788X

会议

会议2017 IEEE International Conference on Multimedia and Expo, ICME 2017
国家/地区香港
Hong Kong
时期10/07/1714/07/17

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